{"id":26794594,"url":"https://github.com/webup/langchain-js-quickstart","last_synced_at":"2025-04-22T18:05:30.120Z","repository":{"id":172469830,"uuid":"640271754","full_name":"webup/langchain-js-quickstart","owner":"webup","description":"LangChain JS 入门示例","archived":false,"fork":false,"pushed_at":"2023-10-08T15:23:28.000Z","size":1768,"stargazers_count":17,"open_issues_count":1,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-29T17:34:01.565Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/webup.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-05-13T14:40:37.000Z","updated_at":"2025-03-04T02:01:19.000Z","dependencies_parsed_at":null,"dependency_job_id":"1dadb3b3-c5ae-46ed-a326-4133b8df30e1","html_url":"https://github.com/webup/langchain-js-quickstart","commit_stats":null,"previous_names":["webup/langchain-js-quickstart"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webup%2Flangchain-js-quickstart","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webup%2Flangchain-js-quickstart/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webup%2Flangchain-js-quickstart/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webup%2Flangchain-js-quickstart/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/webup","download_url":"https://codeload.github.com/webup/langchain-js-quickstart/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250296133,"owners_count":21407037,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-03-29T17:28:12.074Z","updated_at":"2025-04-22T18:05:30.068Z","avatar_url":"https://github.com/webup.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# LangChain JS 中文入门指南示例仓库\n\n欢迎来到 LangChain JS 中文入门指南示例仓库！这个仓库旨在帮助开发者快速上手 [LangChain JS](https://js.langchain.com/docs/) 并熟悉其使用方法。\n\n本仓库是由 [liaokongVFX](https://github.com/liaokongVFX) 编写的 [LangChain 中文入门教程](https://github.com/liaokongVFX/LangChain-Chinese-Getting-Started-Guide) 的 JavaScript 版本。\n\n## LangChain 介绍\n\n[LangChain](https://docs.langchain.com/docs/) 是一个强大的框架，旨在帮助开发人员使用语言模型构建端到端的应用程序。它提供了一套工具、组件和接口，可简化创建由大型语言模型 (LLM) 和聊天模型提供支持的应用程序的过程。LangChain 可以轻松管理与语言模型的交互，将多个组件链接在一起，并集成额外的资源，例如 API 和数据库。\n\n目前官方提供 [Python](https://github.com/hwchase17/langchain) 和 [JavaScript](https://github.com/hwchase17/langchainjs) 两种语言的 SDK。能力上 Python SDK 更为完善。\n\n## 开始使用\n\n1. 首先，克隆本仓库到本地。\n\n2. 接下来，确保您已经安装了 Node.js 和 npm。如果尚未安装，请访问 [Node.js 官方网站](https://nodejs.org/) 下载并安装。\n\n3. 安装项目依赖：`npm install`\n\n4. 为了运行仓库中的样例，您需要安装一个名为 [Node.js Notebooks (REPL)](https://marketplace.visualstudio.com/items?itemName=donjayamanne.typescript-notebook) 的 VS Code 插件。请点击链接，按照插件页面的说明进行安装。\n\n5. 打开 VS Code，然后打开本项目。在项目根目录下，您将看到一个名为 `lab.nnb` 的文件，这个文件包含了多个 LangChain JS 的示例。您可以逐个查看和运行这些示例，学习 LangChain JS 提供的各种功能。\n\n\u003e 注意：请参考 `.env.example` 编写您自己的 `.env` 文件，用于运行相关示例。\n\n## 示例内容\n\n本项目包含以下几个定制示例：\n\n- 直接使用 OpenAI Model 完成一次提问\n- 使用 Agent 通过 Google 搜索并返回答案\n- 使用 Text Loader 对超长文本进行总结和问答\n- 使用内存向量索引数据库构建问答机器人\n- 使用 Pinecone 向量索引库构建问答机器人\n- 使用 Zapier NLA 发送邮件\n\n以及几个官方示例：\n\n- 使用顺序的任务链\n- 使用格式化输出输出\n- 使用 Memory 实现带记忆的对话\n\n## 贡献\n\n我们非常欢迎您为本项目作出贡献！如果您在使用过程中发现了任何问题，或者有任何改进的建议，请通过 Issues 或 Pull Requests 与我们联系。\n\n## 许可证\n\n本仓库采用 [MIT License](LICENSE) 授权。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebup%2Flangchain-js-quickstart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwebup%2Flangchain-js-quickstart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebup%2Flangchain-js-quickstart/lists"}